Prescriptive analytics for transport system management: state-of-the-art development
编号:2380 访问权限:仅限参会人 更新:2021-12-13 17:41:26 浏览:167次 口头报告

报告开始:2021年12月18日 14:50(Asia/Shanghai)

报告时间:25min

所在会场:[S] Special Topic Forums [S3] Emerging Technologies in Tranportation

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摘要
With the development of machine learning algorithm, the advancement of computing equipment, and the increased availability of transportation data, the literature on data-driven optimization for transportation management has been rapidly expanding. Most studies have adopted a two-step approach: in the first step, machine learning models are used to predict the values of uncertain parameters; in the second step, the predicted values are used as input for an optimization model to derive a decision. However, such a two-step approach is flawed in several aspects. In this tutorial, we present recent methodological developments that address the deficiencies of the two-step approach. Hopefully, the theoretical advances can be applied by transportation engineers to solve practical problems.
 
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报告人
Shuaian (Hans) Wang
Department of Logist The Hong Kong Polytechnic University

Dr. Wang is currently Professor at The Hong Kong Polytechnic University (PolyU). Prior to joining PolyU, he worked as a faculty member at Old Dominion University, USA, and the University of Wollongong, Australia. Dr. Wang’s research interests include big data in shipping, green shipping, shipping operations management, port planning and operations, urban transport network modeling, and logistics and supply chain management. Dr. Wang has published over 160 papers in journals such as Transportation Research Part B, Transportation Science, and Operations Research. Dr. Wang is an editor-in-chief of Cleaner Logistics and Supply Chain and Communications in Transportation Research, an associate editor of Transportation Research Part E, Flexible Services and Manufacturing Journal, Transportmetrica A, and Transportation Letters, a handle editor of Transportation Research Record, an editorial board editor of Transportation Research Part B, and an editorial board member of Maritime Transport Research. Dr. Wang dedicates to rethinking and proposing innovative solutions to improve the efficiency of maritime and urban transportation systems, to promote environmental friendly and sustainable practices, and to transform business and engineering education.
 

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重要日期
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    12月17日

    2021

    12月20日

    2021

  • 12月16日 2021

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  • 12月24日 2021

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